Occupancy and presence sensing technology is presently deployed in a variety of contexts. Most individuals are familiar with a passive infrared (PIR) sensor that controls room lights. Many of those individuals have experienced the situation where sitting still for too long causes the lights to shut off. The response is for the individual to wave their arms to provide some motion for the PIR sensor to trigger reactivation of the lights. Similarly, many of those individuals have experienced the situation where merely walking past a room is sufficient to trigger a PIR sensor into determining that a space is occupied, thus causing the lights to turn on despite the absence of any individuals within the space. In the context of lighting, this level of occupancy sensing is sufficient, because the cost (brief lack of lighting and having to wave arms or brief presence of lighting where it is not needed) is relatively inconsequential. However, with the advent of more advanced workspaces that include more complex automated processes, such as room reservations that can automatically adjust based on the occupancy status of a given location, activity/productivity tracking/monitoring that can make determinations regarding how people are utilizing various spaces and/or affordances, and other such processes, more accurate occupancy determinations are needed than those provided by traditional occupancy sensing systems.
Accordingly, a need exists for occupancy sensing systems and methods that are robust in terms of their ability to accurately sense occupancy and are also low cost to make and use.